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RESEARCH PAPER · Advanced Science · 2024

Crystal Composition Transformer: Self‐Learning Neural Language Model for Generative and Tinkering Design of Materials

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Crystal Composition Transformer: Self‐Learning Neural Language Model for Generative and Tinkering Design of MaterialsOriginalProbabilistic generative transformer language models for generative design of molecules22Applications of Transformers in Computational Chemistry: Recent Progress and Prospects11Materials Informatics0Nanoscale Titanium Oxide Memristive Structures for Neuromorphic Applications: Atomic Force Anodization Techniques, Modeling, Chemical Composition, and Resistive Switching Properties2Energy‐Efficient Online Training with In Situ Parallel Computing on Electrochemical Memory Arrays8A perspective on cathode materials for proton-conducting solid oxide fuel cells17Machine learning powered inverse design for strain fields of hierarchical architectures28SLICES-PLUS: A crystal representation leveraging spatial symmetry4A Perspective on Foundation Models in Chemistry58Exploiting Transformer-Based Networks and Boosting Algorithms for Ultralow Compressible Boride Design0MatterGPT: A Generative Transformer for Multi-Property Inverse Design of Solid-State Materials6How Machine Learning Has Driven the Development of Rechargeable Ion Batteries21Rethinking the AI Paradigm for Solubility Prediction of Drug‑Like Compounds with Dual‐Perspective Modeling and Experimental Validation4Large Language Models Meet Molecules: A Systematic Review of Advances and Challenges in AI-Driven Cheminformatics7Machine learning in nanoscience and beyond: Workflows, data processing, XAI and ITAP metrics, language-based models5Artificial intelligence in the development of structural and functional materials: A transformative frontier and complementary enabler of the rational alloy design framework10Deep learning methods for 2D material electronic properties9Large Language Models (LLMs) for Materials Design14Evaluating large language models for inverse semiconductor design0Artificial intelligence-driven approaches for materials design and discovery102Artificial Intelligence in Materials by Design: Critical Review And Perspectives on Materials Informatics to Generative and Agentic Intelligence10Advances in Generative Models for Accelerated Discovery of New Materials1Data-Driven Topological Analysis of Polymorphic Crystal Structures0GrapheneChat: A Large Language Model for Enhancing Graphene Research2Artificial Intelligence for Materials Science: Transforming Research Paradigms6MatterMind: A User‐Friendly Material Design Platform Assisted by Large Language Model0Accelerated customization of nonsymmorphic acoustic metamaterials with topological hierarchy0

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  1. Probabilistic generative transformer language models for generative design of molecules

    Journal of Cheminformatics · 2023-09-25

    Lai Wei, Nihang Fu, Yuqi Song, Qian Wang, Jianjun Hu

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  2. Applications of Transformers in Computational Chemistry: Recent Progress and Prospects

    The Journal of Physical Chemistry Letters · 2024-12-31

    Rui Wang, Youyong Li, Youyong Li, Shuit‐Tong Lee

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  3. Materials Informatics

    Materials horizons · 2025-01-01

    Kritesh Kumar Gupta, Sudip Dey, Tanmoy Mukhopadhyay

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  4. Nanoscale Titanium Oxide Memristive Structures for Neuromorphic Applications: Atomic Force Anodization Techniques, Modeling, Chemical Composition, and Resistive Switching Properties

    Nanomaterials · 2025-01-06

    Авилов Вадим Игоревич, Roman V. Tominov, Zakhar Vakulov, Daniel J. Rodriguez, Nikita V. Polupanov, Vladimir A. Smirnov

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  5. Energy‐Efficient Online Training with In Situ Parallel Computing on Electrochemical Memory Arrays

    Advanced Intelligent Systems · 2025-01-28

    Yingming Lu, Zhen Yang, Yaoyu Tao, Lei Cai, Teng Zhang, Longhao Yan, Ru Huang, Yuchao Yang

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  6. A perspective on cathode materials for proton-conducting solid oxide fuel cells

    International Journal of Hydrogen Energy · 2025-01-31

    Zhiguo Guo, Ling Xu, Yihan Ling, Peixiang Wang, Kangwei Wei, Peng Qiu

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  7. Machine learning powered inverse design for strain fields of hierarchical architectures

    Composites Part B Engineering · 2025-03-19

    Liuchao Jin, Shouyi Yu, Jianxiang Cheng, Zhigang Liu, Kang Zhang, Sicong Zhou, Xiangnan He, Guoquan Xie, Mahdi Bodaghi, Qi Ge, Wei‐Hsin Liao

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  8. SLICES-PLUS: A crystal representation leveraging spatial symmetry

    Materials & Design · 2025-03-20

    Baoning Wang, Zhiyuan Xu, Zhiyu Han, Qiwen Nie, Xi Chen, Hang Xiao, Gang Feng Yan

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  9. A Perspective on Foundation Models in Chemistry

    JACS Au · 2025-03-25

    Junyoung Choi, Gunwook Nam, Jaesik Choi, Yousung Jung

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  10. Exploiting Transformer-Based Networks and Boosting Algorithms for Ultralow Compressible Boride Design

    The Journal of Physical Chemistry C · 2025-04-21

    Edirisuriya M. Dilanga Siriwardane, Rongzhi Dong, Jianjun Hu, Deniz Çakır

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  11. MatterGPT: A Generative Transformer for Multi-Property Inverse Design of Solid-State Materials

    Research Square · 2025-09-05

    Lei Wang, Yan Chen, Xueru Wang, Xiaobin Deng, Yilun Liu, Xi Chen, Jun Zhang, Yunwei Zhang, Hang Xiao

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  12. How Machine Learning Has Driven the Development of Rechargeable Ion Batteries

    Advanced Energy Materials · 2025-09-09

    Huawei Liu, Sihui Li, Shan Zhu, Yin Hu, Xiaopeng Han, Chunsheng Shi, Fang He, He Chunnian, Biao Chen, Naiqin Zhao

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  13. Rethinking the AI Paradigm for Solubility Prediction of Drug‑Like Compounds with Dual‐Perspective Modeling and Experimental Validation

    Advanced Science · 2025-09-25

    Qilin Zhu, Yuxin Qiu, Guzhong Chen, Wenyao Chen, Xiang Zhang, Zhiwen Qi, Xuezhi Duan, De Chen, Zhen Song

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  14. Large Language Models Meet Molecules: A Systematic Review of Advances and Challenges in AI-Driven Cheminformatics

    Archives of Computational Methods in Engineering · 2025-10-21

    Muhammad Saad Umer, Muhammad Nabeel, Usama Athar, Iseult Lynch, Antreas Afantitis, Sami Ullah, Muhammad Moazam Fraz

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  15. Machine learning in nanoscience and beyond: Workflows, data processing, XAI and ITAP metrics, language-based models

    Advances in Colloid and Interface Science · 2025-11-30

    Junnan Song, Qingjie Sun, André G. Skirtach, Bogdan V. Parakhonskiy

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  16. Artificial intelligence in the development of structural and functional materials: A transformative frontier and complementary enabler of the rational alloy design framework

    Next research. · 2025-12-01

    Desmond Edem Primus Klenam

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  17. Deep learning methods for 2D material electronic properties

    Digital Discovery · 2025-12-09

    Artem Mishchenko, Anupam Bhattacharya, Xiangwen Wang, Henry Kelbrick Pentz, Yihao Wei, Qian Yang

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  18. Large Language Models (LLMs) for Materials Design

    Advanced Functional Materials · 2025-12-16

    Lei Zhang, Zhaorui Liu, Ben Ni, Quan Wang

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  19. Evaluating large language models for inverse semiconductor design

    Digital Discovery · 2026-01-01

    Muhammed Nur Talha Kilic, Daniel Wines, Kamal Kumar Choudhary, Vishu Gupta, Youjia Li, Sayak Chakrabarty, Wei‐keng Liao, Choudhary Alok, Ankit Agrawal

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  20. Artificial intelligence-driven approaches for materials design and discovery

    Nature Materials · 2026-01-02

    Mouyang Cheng, Chuliang Fu, Ryotaro Okabe, Abhijatmedhi Chotrattanapituk, Artittaya Boonkird, Nguyen Tuan Hung, Mingda Li

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  21. Artificial Intelligence in Materials by Design: Critical Review And Perspectives on Materials Informatics to Generative and Agentic Intelligence

    Archives of Computational Methods in Engineering · 2026-02-04

    Kritesh Kumar Gupta, Subrata Barman, Anjana Sankar, Sudip Dey, Tanmoy Mukhopadhyay

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  22. Advances in Generative Models for Accelerated Discovery of New Materials

    cScience · 2026-03-01

    Yuan Jiang, Jinshan Li, Zhiqiang Yang, Ningxin Hou, Jun Wang, Bin Tang, Ruihao Yuan

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  23. Data-Driven Topological Analysis of Polymorphic Crystal Structures

    The Journal of Physical Chemistry C · 2026-03-06

    Sourin Dey, Nicholas Miklaucic, Sadman Sadeed Omee, Rongzhi Dong, Lai Wei, Qinyang Li, Nihang Fu, Jianjun Hu

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  24. GrapheneChat: A Large Language Model for Enhancing Graphene Research

    ACS Nano · 2026-03-13

    Dinglong Yang, Chengyu Lu, Yixiong Feng, Weiming Mao, Kang Wang, Luzhao Sun, Yan Wang, Bingtao Hu, Jianrong Tan, Zhongfan Liu, Xiuju Song

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  25. Artificial Intelligence for Materials Science: Transforming Research Paradigms

    Chemical Reviews · 2026-05-20

    Yue Li, Shurui Wang, Jianping Wang, Liu Q, Jin Zhang

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  26. MatterMind: A User‐Friendly Material Design Platform Assisted by Large Language Model

    Materials Genome Engineering Advances · 2026-06-01

    Kaiyang Xu, Yujun Lu, Lifeng Liu, Lei Zhang

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  27. Accelerated customization of nonsymmorphic acoustic metamaterials with topological hierarchy

    International Journal of Mechanical Sciences · 2026-06-11

    Yuyang Chen, Haibing Wang, Zhaoyang Guo, Weizhuo Zhang, Zhengdong Wang, Yu Zhang, Zhiwei Yu, Yijie Liu

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